Dataset statistics

Number of variables	15
Number of observations	279856
Missing cells	18272
Missing cells (%)	0.4%
Duplicate rows	83388
Duplicate rows (%)	29.8%
Total size in memory	32.0 MiB
Average record size in memory	120.0 B

Variable types

Numeric	9
Categorical	5
Boolean	1

Alerts

Dataset has 83388 (29.8%) duplicate rows	Duplicates
`Age` is highly overall correlated with `Income`	High correlation
`City` is highly overall correlated with `State`	High correlation
`Credit Score` is highly overall correlated with `Existing Customer` and 3 other fields	High correlation
`Employment Profile` is highly overall correlated with `Occupation`	High correlation
`Existing Customer` is highly overall correlated with `Credit Score` and 3 other fields	High correlation
`Income` is highly overall correlated with `Age`	High correlation
`LTV Ratio` is highly overall correlated with `Profile Score`	High correlation
`Loan Tenure` is highly overall correlated with `Credit Score` and 3 other fields	High correlation
`Number of Existing Loans` is highly overall correlated with `Credit Score` and 3 other fields	High correlation
`Occupation` is highly overall correlated with `Employment Profile`	High correlation
`Profile Score` is highly overall correlated with `Credit Score` and 4 other fields	High correlation
`State` is highly overall correlated with `City`	High correlation
`Occupation` has 18272 (6.5%) missing values	Missing
`Number of Existing Loans` has 26590 (9.5%) zeros	Zeros

Reproduction

Analysis started	2024-08-04 08:49:54.000181
Analysis finished	2024-08-04 08:50:25.060324
Duration	31.06 seconds
Software version	ydata-profiling vv4.9.0
Download configuration	config.json

Age
Real number (ℝ)

HIGH CORRELATION

Distinct	53
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	44.005217

Minimum	18
Maximum	70
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	18
5-th percentile	20
Q1	31
median	44
Q3	57
95-th percentile	68
Maximum	70
Range	52
Interquartile range (IQR)	26

Descriptive statistics

Standard deviation	15.311051
Coefficient of variation (CV)	0.34793718
Kurtosis	-1.204329
Mean	44.005217
Median Absolute Deviation (MAD)	13
Skewness	-0.0024112255
Sum	12315124
Variance	234.42828
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
55	5540	2.0%
23	5502	2.0%
53	5472	2.0%
36	5459	2.0%
41	5451	1.9%
40	5447	1.9%
52	5441	1.9%
56	5403	1.9%
70	5389	1.9%
24	5383	1.9%
Other values (43)	225369	80.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
18	5311	1.9%
19	5244	1.9%
20	5226	1.9%
21	5361	1.9%
22	5228	1.9%
23	5502	2.0%
24	5383	1.9%
25	5140	1.8%
26	5354	1.9%
27	5370	1.9%

Value	Count	Frequency (%)
70	5389	1.9%
69	5307	1.9%
68	5146	1.8%
67	5311	1.9%
66	5185	1.9%
65	5261	1.9%
64	5298	1.9%
63	5340	1.9%
62	5201	1.9%
61	5169	1.8%

Gender
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.1 MiB

Female	133145
Male	132749
Other	13962

Length

Max length	6
Median length	5
Mean length	5.001415
Min length	4

Characters and Unicode

Total characters	1399676
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Male
2nd row	Male
3rd row	Other
4th row	Female
5th row	Male

Common Values

Value	Count	Frequency (%)
Female	133145	47.6%
Male	132749	47.4%
Other	13962	5.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
female	133145	47.6%
male	132749	47.4%
other	13962	5.0%

Most occurring characters

Value	Count	Frequency (%)
e	413001	29.5%
a	265894	19.0%
l	265894	19.0%
F	133145	9.5%
m	133145	9.5%
M	132749	9.5%
O	13962	1.0%
t	13962	1.0%
h	13962	1.0%
r	13962	1.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1399676	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	413001	29.5%
a	265894	19.0%
l	265894	19.0%
F	133145	9.5%
m	133145	9.5%
M	132749	9.5%
O	13962	1.0%
t	13962	1.0%
h	13962	1.0%
r	13962	1.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1399676	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	413001	29.5%
a	265894	19.0%
l	265894	19.0%
F	133145	9.5%
m	133145	9.5%
M	132749	9.5%
O	13962	1.0%
t	13962	1.0%
h	13962	1.0%
r	13962	1.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1399676	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	413001	29.5%
a	265894	19.0%
l	265894	19.0%
F	133145	9.5%
m	133145	9.5%
M	132749	9.5%
O	13962	1.0%
t	13962	1.0%
h	13962	1.0%
r	13962	1.0%

Income
Real number (ℝ)

HIGH CORRELATION

Distinct	201
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	76499.164

Minimum	9000
Maximum	209000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	9000
5-th percentile	21000
Q1	42000
median	68000
Q3	104000
95-th percentile	160000
Maximum	209000
Range	200000
Interquartile range (IQR)	62000

Descriptive statistics

Standard deviation	42875.575
Coefficient of variation (CV)	0.56047116
Kurtosis	-0.23579952
Mean	76499.164
Median Absolute Deviation (MAD)	29000
Skewness	0.70877886
Sum	2.140875 × 10¹⁰
Variance	1.8383149 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35000	3112	1.1%
37000	3097	1.1%
38000	3069	1.1%
53000	3005	1.1%
44000	2986	1.1%
45000	2977	1.1%
47000	2964	1.1%
42000	2954	1.1%
54000	2945	1.1%
52000	2937	1.0%
Other values (191)	249810	89.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
9000	168	0.1%
10000	416	0.1%
11000	561	0.2%
12000	736	0.3%
13000	927	0.3%
14000	1029	0.4%
15000	1192	0.4%
16000	1381	0.5%
17000	1485	0.5%
18000	1477	0.5%

Value	Count	Frequency (%)
209000	39	< 0.1%
208000	30	< 0.1%
207000	15	< 0.1%
206000	59	< 0.1%
205000	54	< 0.1%
204000	68	< 0.1%
203000	93	< 0.1%
202000	75	< 0.1%
201000	107	< 0.1%
200000	119	< 0.1%

Credit Score
Real number (ℝ)

HIGH CORRELATION

Distinct	551
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	582.95377

Minimum	300
Maximum	850
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	300
5-th percentile	309
Q1	446
median	584
Q3	722
95-th percentile	850
Maximum	850
Range	550
Interquartile range (IQR)	276

Descriptive statistics

Standard deviation	163.07675
Coefficient of variation (CV)	0.27974217
Kurtosis	-1.1255961
Mean	582.95377
Median Absolute Deviation (MAD)	138
Skewness	-0.038313528
Sum	1.6314311 × 10⁸
Variance	26594.028
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
850	15625	5.6%
300	11363	4.1%
438	613	0.2%
401	607	0.2%
412	605	0.2%
537	602	0.2%
770	600	0.2%
756	597	0.2%
502	594	0.2%
390	590	0.2%
Other values (541)	248060	88.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
300	11363	4.1%
301	315	0.1%
302	290	0.1%
303	289	0.1%
304	289	0.1%
305	295	0.1%
306	268	0.1%
307	315	0.1%
308	312	0.1%
309	305	0.1%

Value	Count	Frequency (%)
850	15625	5.6%
849	258	0.1%
848	244	0.1%
847	260	0.1%
846	207	0.1%
845	221	0.1%
844	204	0.1%
843	216	0.1%
842	269	0.1%
841	217	0.1%

Credit History Length
Real number (ℝ)

Distinct	606
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	307.96515

Minimum	6
Maximum	611
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	6
5-th percentile	36
Q1	156
median	307
Q3	460
95-th percentile	581
Maximum	611
Range	605
Interquartile range (IQR)	304

Descriptive statistics

Standard deviation	175.08327
Coefficient of variation (CV)	0.5685165
Kurtosis	-1.2049608
Mean	307.96515
Median Absolute Deviation (MAD)	152
Skewness	0.009495387
Sum	86185894
Variance	30654.151
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
323	572	0.2%
127	568	0.2%
559	567	0.2%
192	554	0.2%
59	550	0.2%
353	549	0.2%
82	542	0.2%
27	541	0.2%
57	540	0.2%
368	540	0.2%
Other values (596)	274333	98.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
6	468	0.2%
7	519	0.2%
8	461	0.2%
9	435	0.2%
10	459	0.2%
11	460	0.2%
12	440	0.2%
13	467	0.2%
14	422	0.2%
15	460	0.2%

Value	Count	Frequency (%)
611	471	0.2%
610	490	0.2%
609	449	0.2%
608	430	0.2%
607	453	0.2%
606	420	0.2%
605	470	0.2%
604	523	0.2%
603	420	0.2%
602	450	0.2%

Number of Existing Loans
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.701693

Minimum	0
Maximum	10
Zeros	26590
Zeros (%)	9.5%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	2
median	5
Q3	7
95-th percentile	10
Maximum	10
Range	10
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	2.9803508
Coefficient of variation (CV)	0.63388885
Kurtosis	-1.1081317
Mean	4.701693
Median Absolute Deviation (MAD)	3
Skewness	0.053826442
Sum	1315797
Variance	8.8824907
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
8	28184	10.1%
4	28059	10.0%
2	27968	10.0%
6	27955	10.0%
5	27950	10.0%
7	27792	9.9%
3	27745	9.9%
0	26590	9.5%
1	24656	8.8%
9	17332	6.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	26590	9.5%
1	24656	8.8%
2	27968	10.0%
3	27745	9.9%
4	28059	10.0%
5	27950	10.0%
6	27955	10.0%
7	27792	9.9%
8	28184	10.1%
9	17332	6.2%

Value	Count	Frequency (%)
10	15625	5.6%
9	17332	6.2%
8	28184	10.1%
7	27792	9.9%
6	27955	10.0%
5	27950	10.0%
4	28059	10.0%
3	27745	9.9%
2	27968	10.0%
1	24656	8.8%

Loan Amount
Real number (ℝ)

Distinct	55681
Distinct (%)	19.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	105795.34

Minimum	5294
Maximum	150000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	5294
5-th percentile	33959
Q1	72173
median	111263
Q3	150000
95-th percentile	150000
Maximum	150000
Range	144706
Interquartile range (IQR)	77827

Descriptive statistics

Standard deviation	40458.371
Coefficient of variation (CV)	0.3824211
Kurtosis	-1.0630462
Mean	105795.34
Median Absolute Deviation (MAD)	38737
Skewness	-0.43901936
Sum	2.9607461 × 10¹⁰
Variance	1.6368798 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
150000	76042	27.2%
51258	20	< 0.1%
127479	15	< 0.1%
56174	15	< 0.1%
138647	15	< 0.1%
54395	15	< 0.1%
104552	15	< 0.1%
91361	15	< 0.1%
137171	15	< 0.1%
137704	15	< 0.1%
Other values (55671)	203674	72.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5294	3	< 0.1%
5319	1	< 0.1%
5514	3	< 0.1%
5684	2	< 0.1%
5985	3	< 0.1%
6221	3	< 0.1%
6267	3	< 0.1%
6501	2	< 0.1%
6549	3	< 0.1%
6568	3	< 0.1%

Value	Count	Frequency (%)
150000	76042	27.2%
149999	3	< 0.1%
149998	5	< 0.1%
149995	3	< 0.1%
149993	2	< 0.1%
149992	5	< 0.1%
149988	6	< 0.1%
149986	4	< 0.1%
149985	6	< 0.1%
149982	3	< 0.1%

Loan Tenure
Real number (ℝ)

HIGH CORRELATION

Distinct	348
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	133.34065

Minimum	12
Maximum	359
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	12
5-th percentile	22
Q1	62
median	100
Q3	201
95-th percentile	328
Maximum	359
Range	347
Interquartile range (IQR)	139

Descriptive statistics

Standard deviation	96.064132
Coefficient of variation (CV)	0.72044144
Kurtosis	-0.49576527
Mean	133.34065
Median Absolute Deviation (MAD)	53
Skewness	0.84222386
Sum	37316182
Variance	9228.3176
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	1971	0.7%
96	1952	0.7%
81	1930	0.7%
63	1921	0.7%
73	1906	0.7%
84	1886	0.7%
94	1881	0.7%
91	1879	0.7%
87	1878	0.7%
114	1878	0.7%
Other values (338)	260774	93.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
12	1476	0.5%
13	1443	0.5%
14	1326	0.5%
15	1306	0.5%
16	1351	0.5%
17	1334	0.5%
18	1258	0.4%
19	1326	0.5%
20	1387	0.5%
21	1446	0.5%

Value	Count	Frequency (%)
359	458	0.2%
358	474	0.2%
357	441	0.2%
356	380	0.1%
355	466	0.2%
354	507	0.2%
353	442	0.2%
352	434	0.2%
351	440	0.2%
350	442	0.2%

Existing Customer
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	273.4 KiB

False	173952
True	105904

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	173952	62.2%
True	105904	37.8%

State
Categorical

HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.1 MiB

Karnataka	28245
Telangana	28101
Maharashtra	28095
Gujarat	28051
West Bengal	28050
Other values (5)	139314

Length

Max length	13
Median length	11
Mean length	8.9965875
Min length	5

Characters and Unicode

Total characters	2517749
Distinct characters	27
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Karnataka
2nd row	Karnataka
3rd row	Uttar Pradesh
4th row	Karnataka
5th row	Karnataka

Common Values

Value	Count	Frequency (%)
Karnataka	28245	10.1%
Telangana	28101	10.0%
Maharashtra	28095	10.0%
Gujarat	28051	10.0%
West Bengal	28050	10.0%
Tamil Nadu	28022	10.0%
Kerala	28011	10.0%
Delhi	27996	10.0%
Uttar Pradesh	27713	9.9%
Rajasthan	27572	9.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
karnataka	28245	7.8%
telangana	28101	7.7%
maharashtra	28095	7.7%
gujarat	28051	7.7%
west	28050	7.7%
bengal	28050	7.7%
tamil	28022	7.7%
nadu	28022	7.7%
kerala	28011	7.7%
delhi	27996	7.7%
Other values (3)	82998	22.8%

Most occurring characters

Value	Count	Frequency (%)
a	644023	25.6%
r	195923	7.8%
t	195439	7.8%
e	167921	6.7%
l	140180	5.6%
n	140069	5.6%
h	139471	5.5%
s	111430	4.4%
	83785	3.3%
K	56256	2.2%
Other values (17)	643252	25.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2517749	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	644023	25.6%
r	195923	7.8%
t	195439	7.8%
e	167921	6.7%
l	140180	5.6%
n	140069	5.6%
h	139471	5.5%
s	111430	4.4%
	83785	3.3%
K	56256	2.2%
Other values (17)	643252	25.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2517749	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	644023	25.6%
r	195923	7.8%
t	195439	7.8%
e	167921	6.7%
l	140180	5.6%
n	140069	5.6%
h	139471	5.5%
s	111430	4.4%
	83785	3.3%
K	56256	2.2%
Other values (17)	643252	25.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2517749	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	644023	25.6%
r	195923	7.8%
t	195439	7.8%
e	167921	6.7%
l	140180	5.6%
n	140069	5.6%
h	139471	5.5%
s	111430	4.4%
	83785	3.3%
K	56256	2.2%
Other values (17)	643252	25.5%

City
Categorical

HIGH CORRELATION

Distinct	23
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.1 MiB

Kolkata	23900
New Delhi	23887
Hyderabad	23726
Mysuru	12227
Udaipur	12012
Other values (18)	184104

Length

Max length	18
Median length	15
Mean length	8.1744576
Min length	4

Characters and Unicode

Total characters	2287671
Distinct characters	37
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mysuru
2nd row	Bengaluru
3rd row	Kanpur
4th row	Bengaluru
5th row	Mysuru

Common Values

Value	Count	Frequency (%)
Kolkata	23900	8.5%
New Delhi	23887	8.5%
Hyderabad	23726	8.5%
Mysuru	12227	4.4%
Udaipur	12012	4.3%
Kanpur	12001	4.3%
Surat	11969	4.3%
Thiruvananthapuram	11966	4.3%
Coimbatore	11907	4.3%
Ahmedabad	11896	4.3%
Other values (13)	124365	44.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kolkata	23900	7.9%
new	23887	7.9%
delhi	23887	7.9%
hyderabad	23726	7.8%
mysuru	12227	4.0%
udaipur	12012	4.0%
kanpur	12001	4.0%
surat	11969	3.9%
thiruvananthapuram	11966	3.9%
coimbatore	11907	3.9%
Other values (14)	136261	44.9%

Most occurring characters

Value	Count	Frequency (%)
a	365947	16.0%
u	180240	7.9%
r	172604	7.5%
i	136639	6.0%
e	135092	5.9%
n	132465	5.8%
h	108425	4.7%
p	88704	3.9%
l	84773	3.7%
d	83256	3.6%
Other values (27)	799526	34.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2287671	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	365947	16.0%
u	180240	7.9%
r	172604	7.5%
i	136639	6.0%
e	135092	5.9%
n	132465	5.8%
h	108425	4.7%
p	88704	3.9%
l	84773	3.7%
d	83256	3.6%
Other values (27)	799526	34.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2287671	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	365947	16.0%
u	180240	7.9%
r	172604	7.5%
i	136639	6.0%
e	135092	5.9%
n	132465	5.8%
h	108425	4.7%
p	88704	3.9%
l	84773	3.7%
d	83256	3.6%
Other values (27)	799526	34.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2287671	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	365947	16.0%
u	180240	7.9%
r	172604	7.5%
i	136639	6.0%
e	135092	5.9%
n	132465	5.8%
h	108425	4.7%
p	88704	3.9%
l	84773	3.7%
d	83256	3.6%
Other values (27)	799526	34.9%

LTV Ratio
Real number (ℝ)

HIGH CORRELATION

Distinct	80874
Distinct (%)	28.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	71.643101

Minimum	40
Maximum	95
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	40
5-th percentile	40
Q1	58.105848
median	72.133017
Q3	86.239725
95-th percentile	95
Maximum	95
Range	55
Interquartile range (IQR)	28.133877

Descriptive statistics

Standard deviation	16.865785
Coefficient of variation (CV)	0.23541394
Kurtosis	-1.0662292
Mean	71.643101
Median Absolute Deviation (MAD)	14.065639
Skewness	-0.18082603
Sum	20049752
Variance	284.45469
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
95	38991	13.9%
40	14388	5.1%
90.94342996	3	< 0.1%
92.20152802	3	< 0.1%
69.42563938	3	< 0.1%
42.50439875	3	< 0.1%
88.03605942	3	< 0.1%
77.64399342	3	< 0.1%
58.86225002	3	< 0.1%
92.53498303	3	< 0.1%
Other values (80864)	226453	80.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
40	14388	5.1%
40.00789025	3	< 0.1%
40.00865185	3	< 0.1%
40.00893284	3	< 0.1%
40.00915752	3	< 0.1%
40.00972416	3	< 0.1%
40.01411194	3	< 0.1%
40.01493892	3	< 0.1%
40.01588615	3	< 0.1%
40.01621929	3	< 0.1%

Value	Count	Frequency (%)
95	38991	13.9%
94.999142	3	< 0.1%
94.99794113	3	< 0.1%
94.99680815	2	< 0.1%
94.99562152	3	< 0.1%
94.99476534	3	< 0.1%
94.99452662	3	< 0.1%
94.99372987	3	< 0.1%
94.99132802	3	< 0.1%
94.99105575	1	< 0.1%

Employment Profile
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.1 MiB

Salaried	136065
Self-Employed	84369
Freelancer	22629
Student	18521
Unemployed	18272

Length

Max length	13
Median length	10
Mean length	9.7334844
Min length	7

Characters and Unicode

Total characters	2723974
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Salaried
2nd row	Salaried
3rd row	Salaried
4th row	Self-Employed
5th row	Salaried

Common Values

Value	Count	Frequency (%)
Salaried	136065	48.6%
Self-Employed	84369	30.1%
Freelancer	22629	8.1%
Student	18521	6.6%
Unemployed	18272	6.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
salaried	136065	48.6%
self-employed	84369	30.1%
freelancer	22629	8.1%
student	18521	6.6%
unemployed	18272	6.5%

Most occurring characters

Value	Count	Frequency (%)
e	427755	15.7%
l	345704	12.7%
a	294759	10.8%
d	257227	9.4%
S	238955	8.8%
r	181323	6.7%
i	136065	5.0%
y	102641	3.8%
o	102641	3.8%
p	102641	3.8%
Other values (10)	534263	19.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2723974	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	427755	15.7%
l	345704	12.7%
a	294759	10.8%
d	257227	9.4%
S	238955	8.8%
r	181323	6.7%
i	136065	5.0%
y	102641	3.8%
o	102641	3.8%
p	102641	3.8%
Other values (10)	534263	19.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2723974	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	427755	15.7%
l	345704	12.7%
a	294759	10.8%
d	257227	9.4%
S	238955	8.8%
r	181323	6.7%
i	136065	5.0%
y	102641	3.8%
o	102641	3.8%
p	102641	3.8%
Other values (10)	534263	19.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2723974	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	427755	15.7%
l	345704	12.7%
a	294759	10.8%
d	257227	9.4%
S	238955	8.8%
r	181323	6.7%
i	136065	5.0%
y	102641	3.8%
o	102641	3.8%
p	102641	3.8%
Other values (10)	534263	19.6%

Profile Score
Real number (ℝ)

HIGH CORRELATION

Distinct	101
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	77.350155

Minimum	0
Maximum	100
Zeros	858
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	2.1 MiB

Quantile statistics

Minimum	0
5-th percentile	28
Q1	61
median	89
Q3	98
95-th percentile	100
Maximum	100
Range	100
Interquartile range (IQR)	37

Descriptive statistics

Standard deviation	24.509196
Coefficient of variation (CV)	0.31686033
Kurtosis	0.041989854
Mean	77.350155
Median Absolute Deviation (MAD)	11
Skewness	-1.0145518
Sum	21646905
Variance	600.70067
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	58495	20.9%
90	8362	3.0%
98	8284	3.0%
95	8257	3.0%
94	8176	2.9%
92	8173	2.9%
96	8012	2.9%
91	7961	2.8%
97	7909	2.8%
99	7852	2.8%
Other values (91)	148375	53.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	858	0.3%
1	119	< 0.1%
2	137	< 0.1%
3	194	0.1%
4	189	0.1%
5	173	0.1%
6	253	0.1%
7	273	0.1%
8	259	0.1%
9	285	0.1%

Value	Count	Frequency (%)
100	58495	20.9%
99	7852	2.8%
98	8284	3.0%
97	7909	2.8%
96	8012	2.9%
95	8257	3.0%
94	8176	2.9%
93	7751	2.8%
92	8173	2.9%
91	7961	2.8%

Occupation
Categorical

HIGH CORRELATION MISSING

Distinct	14
Distinct (%)	< 0.1%
Missing	18272
Missing (%)	6.5%
Memory size	2.1 MiB

Banker	27760
Teacher	27356
Civil Servant	27221
Software Engineer	27146
Doctor	26582
Other values (9)	125519

Length

Max length	22
Median length	16
Mean length	10.028488
Min length	6

Characters and Unicode

Total characters	2623292
Distinct characters	33
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Doctor
2nd row	Software Engineer
3rd row	Banker
4th row	Contractor
5th row	Teacher

Common Values

Value	Count	Frequency (%)
Banker	27760	9.9%
Teacher	27356	9.8%
Civil Servant	27221	9.7%
Software Engineer	27146	9.7%
Doctor	26582	9.5%
Shopkeeper	21405	7.6%
Contractor	21090	7.5%
Farmer	20966	7.5%
Business Owner	20908	7.5%
Student	18521	6.6%
Other values (4)	22629	8.1%
(Missing)	18272	6.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
banker	27760	8.0%
teacher	27356	7.9%
civil	27221	7.8%
servant	27221	7.8%
software	27146	7.8%
engineer	27146	7.8%
doctor	26582	7.6%
shopkeeper	21405	6.1%
contractor	21090	6.1%
farmer	20966	6.0%
Other values (9)	94317	27.1%

Most occurring characters

Value	Count	Frequency (%)
e	376257	14.3%
r	323638	12.3%
n	224563	8.6%
t	188333	7.2%
a	168596	6.4%
o	160935	6.1%
i	119514	4.6%
S	94293	3.6%
	86626	3.3%
c	80751	3.1%
Other values (23)	799786	30.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2623292	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	376257	14.3%
r	323638	12.3%
n	224563	8.6%
t	188333	7.2%
a	168596	6.4%
o	160935	6.1%
i	119514	4.6%
S	94293	3.6%
	86626	3.3%
c	80751	3.1%
Other values (23)	799786	30.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2623292	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	376257	14.3%
r	323638	12.3%
n	224563	8.6%
t	188333	7.2%
a	168596	6.4%
o	160935	6.1%
i	119514	4.6%
S	94293	3.6%
	86626	3.3%
c	80751	3.1%
Other values (23)	799786	30.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2623292	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	376257	14.3%
r	323638	12.3%
n	224563	8.6%
t	188333	7.2%
a	168596	6.4%
o	160935	6.1%
i	119514	4.6%
S	94293	3.6%
	86626	3.3%
c	80751	3.1%
Other values (23)	799786	30.5%

Auto

Heatmap
Table

	Age	City	Credit History Length	Credit Score	Employment Profile	Existing Customer	Gender	Income	LTV Ratio	Loan Amount	Loan Tenure	Number of Existing Loans	Occupation	Profile Score	State
Age	1.000	0.013	0.002	0.125	0.049	0.083	0.000	0.613	-0.040	0.262	0.063	0.123	0.030	0.100	0.008
City	0.013	1.000	0.011	0.012	0.012	0.016	0.005	0.015	0.013	0.013	0.012	0.013	0.013	0.013	0.922
Credit History Length	0.002	0.011	1.000	0.002	0.009	0.013	0.000	0.003	0.001	0.001	-0.003	0.002	0.010	0.000	0.007
Credit Score	0.125	0.012	0.002	1.000	0.056	0.949	0.004	0.208	-0.363	0.083	0.668	0.996	0.034	0.786	0.007
Employment Profile	0.049	0.012	0.009	0.056	1.000	0.058	0.004	0.089	0.019	0.030	0.026	0.053	1.000	0.122	0.007
Existing Customer	0.083	0.016	0.013	0.949	0.058	1.000	0.001	0.149	0.466	0.057	0.681	0.948	0.049	0.675	0.006
Gender	0.000	0.005	0.000	0.004	0.004	0.001	1.000	0.000	0.003	0.005	0.000	0.005	0.002	0.005	0.000
Income	0.613	0.015	0.003	0.208	0.089	0.149	0.000	1.000	-0.067	0.425	0.107	0.206	0.052	0.166	0.007
LTV Ratio	-0.040	0.013	0.001	-0.363	0.019	0.466	0.003	-0.067	1.000	-0.030	-0.239	-0.361	0.013	-0.553	0.009
Loan Amount	0.262	0.013	0.001	0.083	0.030	0.057	0.005	0.425	-0.030	1.000	0.046	0.082	0.019	0.066	0.008
Loan Tenure	0.063	0.012	-0.003	0.668	0.026	0.681	0.000	0.107	-0.239	0.046	1.000	0.664	0.017	0.538	0.007
Number of Existing Loans	0.123	0.013	0.002	0.996	0.053	0.948	0.005	0.206	-0.361	0.082	0.664	1.000	0.032	0.782	0.009
Occupation	0.030	0.013	0.010	0.034	1.000	0.049	0.002	0.052	0.013	0.019	0.017	0.032	1.000	0.073	0.010
Profile Score	0.100	0.013	0.000	0.786	0.122	0.675	0.005	0.166	-0.553	0.066	0.538	0.782	0.073	1.000	0.008
State	0.008	0.922	0.007	0.007	0.007	0.006	0.000	0.007	0.009	0.008	0.007	0.009	0.010	0.008	1.000

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	Age	Gender	Income	Credit Score	Credit History Length	Number of Existing Loans	Loan Amount	Loan Tenure	Existing Customer	State	City	LTV Ratio	Employment Profile	Profile Score	Occupation
0	31	Male	36000	604	487	5	109373	221	No	Karnataka	Mysuru	90.943430	Salaried	77	Doctor
1	25	Male	50000	447	386	2	150000	89	No	Karnataka	Bengaluru	91.135253	Salaried	43	Software Engineer
2	62	Other	178000	850	503	10	69099	110	Yes	Uttar Pradesh	Kanpur	40.000000	Salaried	90	Banker
3	69	Female	46000	668	349	6	150000	148	Yes	Karnataka	Bengaluru	87.393365	Self-Employed	86	Contractor
4	52	Male	132000	601	553	5	150000	157	No	Karnataka	Mysuru	66.158757	Salaried	90	Teacher
5	64	Female	127000	850	158	10	108702	111	Yes	Tamil Nadu	Coimbatore	82.331250	Self-Employed	92	Contractor
6	29	Male	15000	378	89	1	26819	108	No	Uttar Pradesh	Lucknow	95.000000	Self-Employed	25	Farmer
7	30	Other	82000	424	610	2	126550	92	No	West Bengal	Kolkata	93.634577	Salaried	58	Banker
8	52	Male	119000	753	271	8	150000	251	Yes	Rajasthan	Jaipur	75.644166	Freelancer	100	Writer
9	39	Male	101000	575	424	5	113257	12	No	Maharashtra	Nagpur	68.720556	Salaried	87	Banker

	Age	Gender	Income	Credit Score	Credit History Length	Number of Existing Loans	Loan Amount	Loan Tenure	Existing Customer	State	City	LTV Ratio	Employment Profile	Profile Score	Occupation
279846	22	Female	29000	328	185	0	116226	114	No	Gujarat	Ahmedabad	82.980319	Freelancer	34	Photographer
279847	70	Male	158000	621	277	5	94575	329	No	Delhi	New Delhi	68.763160	Salaried	95	Software Engineer
279848	40	Female	48000	555	365	4	129247	82	No	Uttar Pradesh	Manjari	95.000000	Freelancer	60	Independent Consultant
279849	50	Male	72000	300	465	0	150000	59	No	Rajasthan	Jaipur	58.839934	Salaried	67	Banker
279850	53	Female	77000	467	268	3	115186	76	No	Kerala	Thiruvananthapuram	60.563183	Salaried	71	Doctor
279851	69	Male	61000	495	565	3	150000	14	No	Tamil Nadu	Chennai	90.300189	Salaried	71	Software Engineer
279852	45	Female	124000	850	476	10	80341	86	Yes	Karnataka	Bengaluru	78.960607	Salaried	91	Civil Servant
279853	33	Female	71000	582	560	5	39851	101	No	Karnataka	Mysuru	95.000000	Unemployed	57	NaN
279854	67	Male	191000	411	481	2	150000	111	No	Delhi	New Delhi	56.109002	Salaried	69	Software Engineer
279855	33	Other	18000	474	374	3	51522	75	No	Uttar Pradesh	Kanpur	95.000000	Salaried	59	Software Engineer

Most frequently occurring

	Age	Gender	Income	Credit Score	Credit History Length	Number of Existing Loans	Loan Amount	Loan Tenure	Existing Customer	State	City	LTV Ratio	Employment Profile	Profile Score	Occupation	# duplicates
3	18	Female	9000	375	213	1	29082	57	No	Tamil Nadu	Chennai	94.439057	Salaried	31	Software Engineer	3
6	18	Female	9000	484	51	3	41704	103	No	Uttar Pradesh	Lucknow	68.253740	Salaried	100	Doctor	3
9	18	Female	9000	541	119	4	44729	52	No	Kerala	Thiruvananthapuram	82.813109	Unemployed	44	NaN	3
11	18	Female	9000	585	529	5	15970	85	No	West Bengal	Dhulagori	95.000000	Self-Employed	72	Contractor	3
31	18	Female	10000	518	167	3	16758	34	No	Maharashtra	Pune	69.059854	Self-Employed	65	Farmer	3
45	18	Female	11000	300	293	0	45410	102	No	Maharashtra	Nellikuppam	94.786607	Unemployed	24	NaN	3
58	18	Female	11000	755	87	8	15477	250	Yes	Kerala	Kochi	40.000000	Salaried	100	Doctor	3
64	18	Female	12000	407	578	1	21765	14	No	Maharashtra	Nagpur	59.530918	Self-Employed	51	Contractor	3
68	18	Female	12000	477	153	3	27097	32	No	Uttar Pradesh	Nellikuppam	85.558770	Salaried	51	Software Engineer	3
78	18	Female	13000	300	211	0	42491	69	No	Tamil Nadu	Coimbatore	95.000000	Salaried	37	Civil Servant	3

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Interactions

Correlations

Missing values

Sample

Duplicate rows

Most frequently occurring